Send a message to a tmux target. Control characters supported: C-c (stop), C-l (clear), etc.
AI agents invoke send_message to trigger actions in Agent Collaboration MCP Server. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.
This tool sends messages and control characters to tmux sessions running AI agents. It can trigger arbitrary actions in those sessions (including stopping processes via C-c or sending arbitrary input), making it an Execute-category tool. Misuse could disrupt running agents or inject malicious commands, giving it high severity.
From the tool's definition Send a message to a tmux target. Control characters supported: C-c (stop), C-l (clear), etc.
Documented attack patterns abuse exactly the kind of access send_message gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Agent Collaboration MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for send_message:
{
"version": "1",
"default": "deny",
"tools": {
"send_message": {
"limits": [
{
"counter": "send_message_rate",
"window": "minute",
"max": 10,
"scope": "grant"
}
]
}
}
}send_message stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
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Send a message to a tmux target. Control characters supported: C-c (stop), C-l (clear), etc. It is categorised as a Execute tool in the Agent Collaboration MCP Server MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Agent Collaboration MCP Server MCP server in PolicyLayer and add a rule for send_message: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches Agent Collaboration MCP Server. Nothing to install.
send_message is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the send_message rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for send_message. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
send_message is provided by the Agent Collaboration MCP Server MCP server (nishimoto265/agent_collaboration_mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Agent Collaboration MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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6 Agent Collaboration MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.